
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path

from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError

from transformers import AutoFeatureExtractor, WavaVecaFeatureExtractor
from transformers.testing_utils import TOKEN, USER, get_tests_dir, is_staging_test


sys.path.append(str(Path(__file__).parent.parent / 'utils'))

from test_module.custom_feature_extraction import CustomFeatureExtractor  # noqa E402


lowercase    :   Optional[Any]						=			get_tests_dir('fixtures')




class 					lowerCamelCase__				(							unittest.TestCase):




	'''simple docstring'''




	def   _lowerCamelCase							(   self						:Any		)						->					List[Any]:
								# A mock response for an HTTP head request to emulate server down
								__UpperCamelCase      :  Tuple       =   mock.Mock()
								__UpperCamelCase      :  List[str]       =   5_0_0
								__UpperCamelCase      :  Optional[Any]       =   {}
								__UpperCamelCase      :  str       =   HTTPError
								__UpperCamelCase      :  Dict       =   {}

								# Download this model to make sure it's in the cache.
								__UpperCamelCase      :  Tuple       =   WavaVecaFeatureExtractor.from_pretrained("hf-internal-testing/tiny-random-wav2vec2"		)
								# Under the mock environment we get a 500 error when trying to reach the model.
								with mock.patch("requests.Session.request"	,  return_value=a		) as mock_head:
															__UpperCamelCase      :  List[Any]       =   WavaVecaFeatureExtractor.from_pretrained("hf-internal-testing/tiny-random-wav2vec2"		)
															# This check we did call the fake head request
															mock_head.assert_called()







	def   _lowerCamelCase							(   self						:Union[str, Any]		)						->					Union[str, Any]:
								# This test is for deprecated behavior and can be removed in v5
								__UpperCamelCase      :  Dict       =   WavaVecaFeatureExtractor.from_pretrained(
								    "https://huggingface.co/hf-internal-testing/tiny-random-wav2vec2/resolve/main/preprocessor_config.json"		)




@is_staging_test
class 					lowerCamelCase__				(							unittest.TestCase):




	'''simple docstring'''




	@classmethod
	def   _lowerCamelCase							(   cls						:Optional[int]		)						->					int:
								__UpperCamelCase      :  int       =   TOKEN
								HfFolder.save_token(a		)







	@classmethod
	def   _lowerCamelCase							(   cls						:int		)						->					Optional[int]:
								try:
															delete_repo(token=cls._token	,  repo_id="test-feature-extractor"		)
								except HTTPError:
															pass

								try:
															delete_repo(token=cls._token	,  repo_id="valid_org/test-feature-extractor-org"		)
								except HTTPError:
															pass

								try:
															delete_repo(token=cls._token	,  repo_id="test-dynamic-feature-extractor"		)
								except HTTPError:
															pass







	def   _lowerCamelCase							(   self						:Dict		)						->					Optional[Any]:
								__UpperCamelCase      :  Tuple       =   WavaVecaFeatureExtractor.from_pretrained(a		)
								feature_extractor.push_to_hub("test-feature-extractor"	,  use_auth_token=self._token		)

								__UpperCamelCase      :  str       =   WavaVecaFeatureExtractor.from_pretrained(f'{USER}/test-feature-extractor'		)
								for k, v in feature_extractor.__dict__.items():
															self.assertEqual(a	,  getattr(a	,  a		)		)

								# Reset repo
								delete_repo(token=self._token	,  repo_id="test-feature-extractor"		)

								# Push to hub via save_pretrained
								with tempfile.TemporaryDirectory() as tmp_dir:
															feature_extractor.save_pretrained(
															    a	,  repo_id="test-feature-extractor"	,  push_to_hub=a	,  use_auth_token=self._token		)

								__UpperCamelCase      :  int       =   WavaVecaFeatureExtractor.from_pretrained(f'{USER}/test-feature-extractor'		)
								for k, v in feature_extractor.__dict__.items():
															self.assertEqual(a	,  getattr(a	,  a		)		)







	def   _lowerCamelCase							(   self						:Optional[Any]		)						->					Optional[int]:
								__UpperCamelCase      :  Optional[Any]       =   WavaVecaFeatureExtractor.from_pretrained(a		)
								feature_extractor.push_to_hub("valid_org/test-feature-extractor"	,  use_auth_token=self._token		)

								__UpperCamelCase      :  Dict       =   WavaVecaFeatureExtractor.from_pretrained("valid_org/test-feature-extractor"		)
								for k, v in feature_extractor.__dict__.items():
															self.assertEqual(a	,  getattr(a	,  a		)		)

								# Reset repo
								delete_repo(token=self._token	,  repo_id="valid_org/test-feature-extractor"		)

								# Push to hub via save_pretrained
								with tempfile.TemporaryDirectory() as tmp_dir:
															feature_extractor.save_pretrained(
															    a	,  repo_id="valid_org/test-feature-extractor-org"	,  push_to_hub=a	,  use_auth_token=self._token		)

								__UpperCamelCase      :  Union[str, Any]       =   WavaVecaFeatureExtractor.from_pretrained("valid_org/test-feature-extractor-org"		)
								for k, v in feature_extractor.__dict__.items():
															self.assertEqual(a	,  getattr(a	,  a		)		)







	def   _lowerCamelCase							(   self						:Optional[Any]		)						->					Dict:
								CustomFeatureExtractor.register_for_auto_class()
								__UpperCamelCase      :  Any       =   CustomFeatureExtractor.from_pretrained(a		)

								feature_extractor.push_to_hub("test-dynamic-feature-extractor"	,  use_auth_token=self._token		)

								# This has added the proper auto_map field to the config
								self.assertDictEqual(
								    feature_extractor.auto_map	,  {"AutoFeatureExtractor": "custom_feature_extraction.CustomFeatureExtractor"}	,  )

								__UpperCamelCase      :  str       =   AutoFeatureExtractor.from_pretrained(
								    f'{USER}/test-dynamic-feature-extractor'	,  trust_remote_code=a		)
								# Can't make an isinstance check because the new_feature_extractor is from the CustomFeatureExtractor class of a dynamic module
								self.assertEqual(new_feature_extractor.__class__.__name__	,  "CustomFeatureExtractor"		)

from __future__ import annotations




class 					lowerCamelCase__				:




	'''simple docstring'''




	def __init__(   self						:Dict	,  a						:str	,  a						:str		)						->					Union[str, Any]:
								__UpperCamelCase  ,		__UpperCamelCase      :  Optional[int]       =   text, pattern
								__UpperCamelCase  ,		__UpperCamelCase      :  Tuple       =   len(a		), len(a		)







	def   _lowerCamelCase							(   self						:Any	,  a						:str		)						->					int:

								for i in range(self.patLen - 1	,  -1	,  -1		):
															if char == self.pattern[i]:
																						return i
								return -1







	def   _lowerCamelCase							(   self						:str	,  a						:int		)						->					int:

								for i in range(self.patLen - 1	,  -1	,  -1		):
															if self.pattern[i] != self.text[current_pos + i]:
																						return current_pos + i
								return -1







	def   _lowerCamelCase							(   self						:Union[str, Any]		)						->					list[int]:
								# searches pattern in text and returns index positions
								__UpperCamelCase      :  Any       =   []
								for i in range(self.textLen - self.patLen + 1		):
															__UpperCamelCase      :  List[Any]       =   self.mismatch_in_text(a		)
															if mismatch_index == -1:
																						positions.append(a		)
															else:
																						__UpperCamelCase      :  Any       =   self.match_in_pattern(self.text[mismatch_index]		)
																						__UpperCamelCase      :  Dict       =   (
																						    mismatch_index - match_index
																						)  # shifting index lgtm [py/multiple-definition]
								return positions
lowercase    :   Any						=			'ABAABA'
lowercase    :   str						=			'AB'
lowercase    :   str						=			BoyerMooreSearch(text, pattern)
lowercase    :   Union[str, Any]						=			bms.bad_character_heuristic()

if len(positions) == 0:
		print('No match found')
else:
		print('Pattern found in following positions: ')
		print(positions)